A Deep Learning Based Approach for Context-Aware Multi-Criteria Recommender Systems

Recommender systems are similar to an informationfiltering system that helps identify items that best satisfy the users’demands based on their pre-ference profiles.Context-aware recommender systems(CARSs)and multi-criteria recommender systems(MCRSs)are extensions of traditional recommender sys-tems.CARSs have integrated additional contextual information such as time,place,and so on for providing better recommendations.However,the majority of CARSs use ratings as a unique criterion for building communities.Meanwhile,MCRSs utilize user preferences in multiple criteria to better generate recommen-dations.Up to now,how to exploit context in MCRSs is still an open issue.This paper proposes a novel approach,which relies on deep learning for context-aware multi-criteria recommender systems.We apply deep neural network(DNN)mod-els to predict the context-aware multi-criteria ratings and learn the aggregation function.We conduct experiments to evaluate the effect of this approach on the real-world dataset.A significant result is that our method outperforms other state-of-the-art methods for recommendation effectiveness.

Relevant Visual Semantic Context-Aware Attention-Based Dialog

The existing dataset for visual dialog comprises multiple rounds of questions and a diverse range of image contents.However,it faces challenges in overcoming visual semantic limitations,particularly in obtaining sufficient context from visual and textual aspects of images.This paper proposes a new visual dialog dataset called Diverse History-Dialog(DS-Dialog)to address the visual semantic limitations faced by the existing dataset.DS-Dialog groups relevant histories based on their respective Microsoft Common Objects in Context(MSCOCO)image categories and consolidates them for each image.Specifically,each MSCOCO image category consists of top relevant histories extracted based on their semantic relationships between the original image caption and historical context.These relevant histories are consolidated for each image,and DS-Dialog enhances the current dataset by adding new context-aware relevant history to provide more visual semantic context for each image.The new dataset is generated through several stages,including image semantic feature extraction,keyphrase extraction,relevant question extraction,and relevant history dialog generation.The DS-Dialog dataset contains about 2.6 million question-answer pairs,where 1.3 million pairs correspond to existing VisDial’s question-answer pairs,and the remaining 1.3 million pairs include a maximum of 5 image features for each VisDial image,with each image comprising 10-round relevant question-answer pairs.Moreover,a novel adaptive relevant history selection is proposed to resolve missing visual semantic information for each image.DS-Dialog is used to benchmark the performance of previous visual dialog models and achieves better performance than previous models.Specifically,the proposed DSDialog model achieves an 8% higher mean reciprocal rank(MRR),11% higher R@1%,6% higher R@5%,5% higher R@10%,and 8% higher normalized discounted cumulative gain(NDCG)compared to LF.DS-Dialog also achieves approximately 1 point improvement on R@k,mean,MRR,and NDCG compared to the original RVA,and 2 points improvement compared to LF andDualVD.These results demonstrates the importance of the relevant semantic historical context in enhancing the visual semantic relationship between textual and visual representations of the images and questions.

Improving Recommendation for Effective Personalization in Context-Aware Data Using Novel Neural Network

The digital technologies that run based on users’content provide a platform for users to help air their opinions on various aspects of a particular subject or product.The recommendation agents play a crucial role in personalizing the needs of individual users.Therefore,it is essential to improve the user experience.The recommender system focuses on recommending a set of items to a user to help the decision-making process and is prevalent across e-commerce and media websites.In Context-Aware Recommender Systems(CARS),several influential and contextual variables are identified to provide an effective recommendation.A substantial trade-off is applied in context to achieve the proper accuracy and coverage required for a collaborative recommendation.The CARS will generate more recommendations utilizing adapting them to a certain contextual situation of users.However,the key issue is how contextual information is used to create good and intelligent recommender systems.This paper proposes an Artificial Neural Network(ANN)to achieve contextual recommendations based on usergenerated reviews.The ability of ANNs to learn events and make decisions based on similar events makes it effective for personalized recommendations in CARS.Thus,the most appropriate contexts in which a user should choose an item or service are achieved.This work converts every label set into a Multi-Label Classification(MLC)problem to enhance recommendations.Experimental results show that the proposed ANN performs better in the Binary Relevance(BR)Instance-Based Classifier,the BR Decision Tree,and the Multi-label SVM for Trip Advisor and LDOS-CoMoDa Dataset.Furthermore,the accuracy of the proposed ANN achieves better results by 1.1%to 6.1%compared to other existing methods.

The neurovascular unit-on-a-chip:modeling ischemic stroke to stem cell therapy

The neurovascular unit and stem cell therapy in ischemic stroke:Ischemic stroke,accounts for approximately 85% of all stroke incidents and is a major global health burden.It is the leading cause of disability and death worldwide,posing immense societal and economic challenges due to the long-term care required for stro ke survivors and the significant healthcare costs associated with its treatment and management(Amarenco et al.,2009).

Risk Factors for Mortality in Acute Kidney Injury in Intensive Care Units in Togo

Context: Acute kidney injury (AKI) in intensive care unit (ICU) is common and associated with very high mortality. In Togo, a tropical country with limited resources and only one nephrology department in the north, acute kidney injury seems to be a real tragedy with high mortality. Aims: to determine risk factors for mortality in acute kidney injury in the intensive care units. Methods and Material: We made a multicentric cross sectional study during 6 months in the four referral centers in northern Togo. Univariate and multivariate logistic regression was used to identify factors associated with mortality. Data were analyzed using RStudio 2023.04.1. Results: A total of 12.6% of patients admitted to intensive care had presented with AKI. The mean age was 49.6 ± 17.9. The sex ratio (M/F) was 2.1. Community-acquired AKI was in the majority (67.7%). Oligo anuria was the most frequent functional sign (38.4%). In our series, 81.6% of patients were in KDIGO stages 2 to 3. AKI was organic in 56.2% of cases. Mortality was 44.3%. In multivariate analysis, the main factors predictive of death were: respiratory distress (OR = 2.36;p Conclusions: Acute kidney injury in intensive care is common in northern Togo, and mortality is high. Identification of associated factors should help anticipate prognosis.

A Retrospective Analysis of Intoxicated Patients Admitted to the Intensive Care Unit: A Single-Institution Assessment in the Post-Pandemic Period

Background: The aim of this study was to evaluate the clinical and epidemiological characteristics of patients with acute intoxication admitted to the Intensive Care Unit (ICU). Material and Methods: An observational retrospective study was conducted on intoxicated patients who admitted to ICU between January 2022 and January 2024. Data were collected from the patients medical records. The demographic characteristics, causes of intoxications, clinical parameters, the mean stay in the ICU, treatment modalities and prognosis were recorded. Results: A total of 2875 critically ill patients were admitted during the study period, and 109 (3.79%) of them were acute intoxications. Their mean of ages was 38.09 ± 12.29. The female-to-male ratio was 1.37/1. Drugs were found to be the primary cause (62.39%) of intoxications, and analgesics, antidepressants, and antibiotics were the most frequent agents. Suicidal attempts were present in 66 patients, most of them were female (62.13%) and between 17 - 24 years (40.91%). The other common causes of intoxications were carbon monoxide (CO) (22.02%), methyl/ethyl alcohol (8.26%) and mushroom (5.50%). The mean stay in the ICU was 2.69 ± 0.89 days. Mechanical ventilation was applied to 10 of our patients. Renal replacement therapy was required in 6 patients. Despite all treatments, 6 of our patients died, and we found the mortality rate to be 5.50%. Conclusion: Intoxications were more frequent in young female patients and drugs were the most common cause with suicidal intent. Unfortunately, CO poisoning continues to be a very important problem in our city. These findings provided significant information about the characteristics of intoxications in Karabuk.

基于Unity3D的油田抽油机三维可视化监控系统设计

针对抽油机监测形式单一、三维可视化程度低和联动性差的缺陷,引入信息―物理实时映射思想,开发了油田抽油机三维可视化监控系统。设计了抽油机数字空间,搭建虚实交互层设计架构;搭建三维可视化系统数据组成及关系框架;结合逆运动学,构建数学模型,基于五维模型和Unity 3D平台设计抽油机三维可视化系统总体架构;以游梁式抽油机为对象进行实验验证,实现了实时动态监测、虚实混合控制、运动轨迹追踪和在线预警等服务功能。为三维可视化监控在石油机械领域的落地应用和数字孪生系统的开发提供借鉴。

Sustained release of vascular endothelial growth factor A and basic fibroblast growth factor from nanofiber membranes reduces oxygen/glucose deprivation-induced injury to neurovascular units

Upregulation of vascular endothelial growth factor A/basic fibroblast growth factor(VEGFA/b FGF)expression in the penumbra of cerebral ischemia can increase vascular volume,reduce lesion volume,and enhance neural cell proliferation and differentiation,thereby exerting neuroprotective effects.However,the beneficial effects of endogenous VEGFA/b FGF are limited as their expression is only transiently increased.In this study,we generated multilayered nanofiber membranes loaded with VEGFA/b FGF using layer-by-layer self-assembly and electrospinning techniques.We found that a membrane containing 10 layers had an ideal ultrastructure and could efficiently and stably release growth factors for more than 1 month.This 10-layered nanofiber membrane promoted brain microvascular endothelial cell tube formation and proliferation,inhibited neuronal apoptosis,upregulated the expression of tight junction proteins,and improved the viability of various cellular components of neurovascular units under conditions of oxygen/glucose deprivation.Furthermore,this nanofiber membrane decreased the expression of Janus kinase-2/signal transducer and activator of transcription-3(JAK2/STAT3),Bax/Bcl-2,and cleaved caspase-3.Therefore,this nanofiber membrane exhibits a neuroprotective effect on oxygen/glucose-deprived neurovascular units by inhibiting the JAK2/STAT3 pathway.

Assessment of Wet Season Precipitation in the Central United States by the Regional Climate Simulation of the WRFG Member in NARCCAP and Its Relationship with Large-Scale Circulation Biases

Assessment of past-climate simulations of regional climate models(RCMs)is important for understanding the reliability of RCMs when used to project future regional climate.Here,we assess the performance and discuss possible causes of biases in a WRF-based RCM with a grid spacing of 50 km,named WRFG,from the North American Regional Climate Change Assessment Program(NARCCAP)in simulating wet season precipitation over the Central United States for a period when observational data are available.The RCM reproduces key features of the precipitation distribution characteristics during late spring to early summer,although it tends to underestimate the magnitude of precipitation.This dry bias is partially due to the model’s lack of skill in simulating nocturnal precipitation related to the lack of eastward propagating convective systems in the simulation.Inaccuracy in reproducing large-scale circulation and environmental conditions is another contributing factor.The too weak simulated pressure gradient between the Rocky Mountains and the Gulf of Mexico results in weaker southerly winds in between,leading to a reduction of warm moist air transport from the Gulf to the Central Great Plains.The simulated low-level horizontal convergence fields are less favorable for upward motion than in the NARR and hence,for the development of moist convection as well.Therefore,a careful examination of an RCM’s deficiencies and the identification of the source of errors are important when using the RCM to project precipitation changes in future climate scenarios.

Analysis of the Erosion-Corrosion Mechanism of the Air Cooler in a Hydrocracking Unit:A Numerical and Experimental Study

Corrosion leakages often occur in the air cooler of a hydrocracking unit,with the failure sites mainly located in the entrance area of the tubes.An analysis of the macroscopic morphology and corrosion products confirmed that the damage was caused by erosion-corrosion(E-C).Numerical and experimental methods were applied to investigate the E-C mechanism in the air cooler.Computational fluid dynamics(CFD)was used to calculate the hydrodynamic parameters of the air cooler.The results showed that there was a biased flow in the air cooler,which led to a significant increase in velocity,turbulent kinetic energy and wall shear within 0.2 m of the tube entrance.A visualization experiment was then performed to determine the principles of migration and transformation of multiphase flow in the air cooler tubes.Various flow patterns(pure droplet flow,mist flow,and annular flow)and their evolutionary processes were clearly depicted experimentally.The initiation mechanism and processes leading to the development of E-C in the air cooler were also determined.This study provided a comprehensive explanation for the E-C failures that occur in air coolers during operation.

Bionic lightweight design of limb leg units for hydraulic quadruped robots by additive manufacturing and topology optimization

Galloping cheetahs,climbing mountain goats,and load hauling horses all show desirable locomotion capability,which motivates the development of quadruped robots.Among various quadruped robots,hydraulically driven quadruped robots show great potential in unstructured environments due to their discrete landing positions and large payloads.As the most critical movement unit of a quadruped robot,the limb leg unit(LLU)directly affects movement speed and reliability,and requires a compact and lightweight design.Inspired by the dexterous skeleton–muscle systems of cheetahs and humans,this paper proposes a highly integrated bionic actuator system for a better dynamic performance of an LLU.We propose that a cylinder barrel with multiple element interfaces and internal smooth channels is realized using metal additive manufacturing,and hybrid lattice structures are introduced into the lightweight design of the piston rod.In addition,additive manufacturing and topology optimization are incorporated to reduce the redundant material of the structural parts of the LLU.The mechanical properties of the actuator system are verified by numerical simulation and experiments,and the power density of the actuators is far greater than that of cheetah muscle.The mass of the optimized LLU is reduced by 24.5%,and the optimized LLU shows better response time performance when given a step signal,and presents a good trajectory tracking ability with the increase in motion frequency.

Petrogenesis and Tectonic Implications of the Early Triassic Nianzi Adakitic Granite Unit in the Yanshan Fold and Thrust Belt:New Constraints from U-Pb Geochronology and Sr-Nd-Hf Isotopes

The Nianzi granite unit,which includes the Nianzi,Xiaolianghou and Xiawopu granitic intrusions,is a significant component of the northern part of the North China Craton(NCC)and is situated in the Yanshan fold and thrust belt(YFTB).However,there is still debate regarding the tectonic evolutionary history of the YFTB during the late Permian to Triassic period,specifically regarding the timing of subduction and collision between the NCC and the Paleo-Asian Ocean.The Nianzi granite unit exhibits unique petrological,geochronological and geochemical signatures that shed light on the tectonic evolutionary history of the YFTB.This study presents detailed petrology,whole-rock geochemistry,together with Sr-Nd isotopic,zircon U-Pb dating and Lu-Hf isotopic data of the granites within the Nianzi granite unit.Our findings demonstrate that the granites primarily consist of subhedral K-feldspar,plagioclase,quartz,minor biotite and hornblende,with accessory titanite,apatite,magnetite and zircon.Zircon U-Pb dating indicates that the Xiaolianghou granite was emplaced at 247.5±0.62 Ma.Additionally,the adakitic characteristics of the Nianzi,Xiawopu and Xiaolianghou granitic intrusions,such as high Sr and Ba contents and high ratios of Sr/Y and(La/Yb)N,combined with negative Sr-Nd and Lu-Hf isotopes(87Sr/86Sr)i=0.705681–0.7057433,εNd(t)=−21.98 to−20.97,zirconεHf(t)=−20.26 to−9.92,as well as the I-type granite features of high SiO_(2),Na_(2)O and K_(2)O/Na_(2)O ratios,enriched Rb,K,Sr and Ba,along with depleted Th,U,Nb,Ta,P and Ti,suggest that the Nianzi granitic unit was mainly derived from the partial melting of a thickened lower crust containing hydrous,calc-alkaline to high-K calc-alkaline,mafic to intermediate metamorphic rocks.In light of these parameters,we further integrate our data with previous studies and conclude that the Nianzi granitic unit was generated in a post-collisional extensional environment during the Early Triassic.

Improvement of the nutritional support management system for patients in intensive care units

BACKGROUND Nutritional support for patients hospitalized in the intensive care unit(ICU)is an important part of clinical treatment and care,but there are significant implementation difficulties.AIM To introduce a modified nutritional support management system for ICU patients based on closed-loop information management and psychological counseling.METHODS The division of functions,personnel training,system construction,development of an intelligent decision-making software system,quality control,and improvement of the whole process were carried out to systematically manage nutritional support for ICU patients.RESULTS Following the implementation of the whole process management system,the scores of ICU medical staff’s knowledge,attitudes/beliefs,and practices regarding nutritional support were comprehensively enhanced.The proportion of hospital bed-days of total enteral nutrition(EN)in ICU patients increased from 5.58%to 11.46%,and the proportion of EN plus parenteral nutrition increased from 42.71%to 47.07%.The rate of EN initiation within 48 h of ICU admission increased from 37.50%to 48.28%,and the EN compliance rate within 72 h elevated from 20.59%to 31.72%.After the implementation of the project,the Self-rating Anxiety Scale score decreased from 61.07±9.91 points to 52.03±9.02 points,the Self-rating Depression Scale score reduced from 62.47±10.50 points to 56.34±9.83 points,and the ICU stay decreased from 5.76±2.77 d to 5.10±2.12 d.CONCLUSION The nutritional support management system based on closed-loop information management and psychological counseling achieved remarkable results in clinical applications in ICU patients.

Aerial target threat assessment based on gated recurrent unit and self-attention mechanism

Aerial threat assessment is a crucial link in modern air combat, whose result counts a great deal for commanders to make decisions. With the consideration that the existing threat assessment methods have difficulties in dealing with high dimensional time series target data, a threat assessment method based on self-attention mechanism and gated recurrent unit(SAGRU) is proposed. Firstly, a threat feature system including air combat situations and capability features is established. Moreover, a data augmentation process based on fractional Fourier transform(FRFT) is applied to extract more valuable information from time series situation features. Furthermore, aiming to capture key characteristics of battlefield evolution, a bidirectional GRU and SA mechanisms are designed for enhanced features.Subsequently, after the concatenation of the processed air combat situation and capability features, the target threat level will be predicted by fully connected neural layers and the softmax classifier. Finally, in order to validate this model, an air combat dataset generated by a combat simulation system is introduced for model training and testing. The comparison experiments show the proposed model has structural rationality and can perform threat assessment faster and more accurately than the other existing models based on deep learning.

A gated recurrent unit model to predict Poisson’s ratio using deep learning

Static Poisson’s ratio(vs)is crucial for determining geomechanical properties in petroleum applications,namely sand production.Some models have been used to predict vs;however,the published models were limited to specific data ranges with an average absolute percentage relative error(AAPRE)of more than 10%.The published gated recurrent unit(GRU)models do not consider trend analysis to show physical behaviors.In this study,we aim to develop a GRU model using trend analysis and three inputs for predicting n s based on a broad range of data,n s(value of 0.1627-0.4492),bulk formation density(RHOB)(0.315-2.994 g/mL),compressional time(DTc)(44.43-186.9 μs/ft),and shear time(DTs)(72.9-341.2μ s/ft).The GRU model was evaluated using different approaches,including statistical error an-alyses.The GRU model showed the proper trends,and the model data ranges were wider than previous ones.The GRU model has the largest correlation coefficient(R)of 0.967 and the lowest AAPRE,average percent relative error(APRE),root mean square error(RMSE),and standard deviation(SD)of 3.228%,1.054%,4.389,and 0.013,respectively,compared to other models.The GRU model has a high accuracy for the different datasets:training,validation,testing,and the whole datasets with R and AAPRE values were 0.981 and 2.601%,0.966 and 3.274%,0.967 and 3.228%,and 0.977 and 2.861%,respectively.The group error analyses of all inputs show that the GRU model has less than 5% AAPRE for all input ranges,which is superior to other models that have different AAPRE values of more than 10% at various ranges of inputs.

Epidemiology of carbapenem-resistant Acinetobacter baumannii colonization in neonatal intensive care units:A systematic review and meta-analysis

BACKGROUND The rising prevalence of carbapenem-resistant Acinetobacter baumannii(CRAB)in neonatal intensive care units(NICUs)represents an escalating challenge in healthcare settings,particularly in managing hospital-acquired infections(HAIs).Studies across various World Health Organization regions have documented a significant incidence of CRAB-related HAIs,with rates as high as 41.7 cases per 1000 patients in ICUs,accounting for 13.6%of all HAIs.These infections pose a doubled mortality risk compared to infections with carbapenem-susceptible Acinetobacter baumannii.A particularly concerning aspect of CRAB colonization is its asymptomatic nature,enabling its transmission through healthcare workers(HCWs)or the NICU environment to vulnerable neonates with developing immune systems.AIM To explore the prevalence of CRAB colonization in NICUs,focusing on neonates,healthcare workers,and the environmental samples,to enhance epidemiological understanding and inform targeted interventions.METHODS We conducted according to PRISMA 2020 checklist guidelines,a comprehensive literature search across multiple databases including MEDLINE(Ovid),EMBASE(Ovid),Global Health(Ovid),Web of Science,and Global Index Me-dicus.Studies were selected based on predetermined criteria,primarily involving neonates,HCWs,and environmental swabs,using culture or molecular methods to detect CRAB colonization.We excluded studies that did not specifically focus on NICUs,were duplicates,or lacked necessary data.The study selection and quality assessment were conducted independently by two reviewers.Data extraction involved collecting comprehensive details about each study.Our statistical analysis used a random-effects model to calculate the pooled prevalence and confidence intervals,stratifying results by regional location.We assessed study heterogeneity using Cochran's Q statistic and I²statistic,with regression tests employed to evaluate potential publication bias.RESULTS We analyzed 737 records from five databases,ultimately including 13 studies from ten countries.For neonates,the pooled prevalence was 4.8%(95%CI:1.1%to 10.5%)with the highest rates observed in South-East Asia(10.5%;95%CI:2.4%to 23.3%).Among HCWs,a single Indian study reported a 3.3%prevalence.Environmental samples showed a prevalence of 2.3%(95%CI:0%to 9.3%),with the highest rates in South-East Asia(10%;95%CI:4.2%to 17.7%).Significant heterogeneity was found across studies,and no publication bias was detected.CONCLUSION This systematic review highlights a significant prevalence of CRAB colonization in neonates across various regions,particularly in South-East Asia,contrasting with lower rates in high-income countries.The study reveals a gap in research on HCWs colonization,with only a single study from India reporting moderate prevalence.Environmental samples indicate moderate levels of CRAB contamination,again higher in South-East Asia.These findings underscore the need for more extensive and focused research on CRAB colonization in NICUs,including exploring the roles of HCWs and the environment in transmission,understanding antimicrobial resistance patterns,and developing effective prevention measures.

Delayed Grafting as a Valid Technique in Burn Management: Experience from a Burn Unit in Oman

Background: Early excision and grafting has been the preferred method of managing major burns around the world since 1970. Considering the advances in health care and the development of new antibiotics over the past 50 years, delayed grafting as a technique for the management of burns over 15%-20% of total body surface area (TBSA) could have comparable results to that of early excision. This study aims to highlight the outcomes of practicing delayed grafting in burn patients. Methods: A case series analysis was performed of 51 patients who were admitted to the burns unit in Sultan Qaboos Hospital Salalah with over 20% TBSA between January 2014 and December 2019. The patients received prophylactic antibiotics and silver sulphadiazine dressing until the burn eschar had completely separated, followed by grafting. Results: Two patients were lost during the entire duration of the study. The mortality rate was comparable to that of early excision, while the rate of hypertrophic scarring was lower than the range reported by other studies. Conclusion: In the management of patients with over 20% TBSA, delayed grafting after complete separation of eschar is still a valid technique.

Temperature Trends and Accumulation of Chill Hours, Chill Units, and Chill Portions in South Carolina

There is considerable concern about the potential impact of climate change on agriculture, such as the accumulation of chilling hours needed to break the dormancy of many perennial plants, like fruit trees. Therefore, this study aimed to determine if there had been a significant change in air temperatures and chill hours, chill units, and chill portion accumulation in South Carolina over the last two decades. Two decades of daily maximum (Tmax) and minimum (Tmin) air temperature records were obtained from weather stations in thirty-one counties in South Carolina. Hourly temperature data, reconstructed from the daily data, were used to calculate the daily and annual chill hours, chill units, and chill portions accumulation using four different chill models for each location and year. The chill models included the T(t) °C model, the 0°C °C model, the Utah model, and the Dynamic model. For each county, regression analyses were conducted to evaluate the historical trends. Despite year-to-year variability, the tendency was a statistically significant (α = 0.05) increase in air temperature, averaging 0.089°C per year for 20 out of 31 counties in South Carolina. The other 11 counties had no significant change in temperature. The average temperature increase in the 31 counties was 0.072°C per year. The temperature increase resulted in a decrease in annual chill accumulation during the fall to spring, averaging 17.7 chill hours, 8.6 chill hours, 17.0 chill units, and 0.40 chill portions per year calculated with the T(t) °C, 0°C °C, Utah, and Dynamic models, respectively. However, whether this decrease in chill values was statistically significant or not depended on the chill model used. This study did not investigate the cause of the observed historical trends in temperature and chill accumulation. Still, if the trends continue, they could significantly impact the future of the temperate fruit tree industry in the state.

Improved Units of Measure in Rotational Mechanics

The SI system of units in rotational mechanics yields correct numerical results, but it produces physically incorrect units of measure in many cases. SI units also violate the principle of general covariance—the general rule for defining continuous coordinates and units in mathematics and mathematical physics. After 30+ years of wrestling with these problems, the ultimate authority on units of measure has declared that Newton–meter and Joule are not equivalent in rotational mechanics, as they are in the rest of physics. This article proposes a simple modification to SI units called “Nonstandard International units” (“NI units”) until a better name is agreed upon. NI units yield correct numerical results and physically correct units of measure, and they satisfy the principle of general covariance. The main obstacle to the adoption of NI units is the consensus among users that the radius of rotation should have the unit meter because the radius can be measured with a ruler. NI units assigned to radius should have units meter/radian because the radius is a conversion factor between angular size and circumferential length, as in arclength = rθ. To manage the social consensus behind SI units, the author recommends retaining SI units as they are, and informing users who want correct units that NI units solve the technical problems of SI units.

Context-Aware Technology of Disabled Health Service for Intelligent Community

With the rapid development of Ubiquitous computing,context-aware technology as one of the core contents of the former has made a series of research progress and achievements.Context-aware technology can automatically provide the corresponding services according to the strategy given by the inference engine through sensing the related context of the environment and tasks.It is because context-aware technology can significantly improve the intelligence of computer interaction,the application of this technology to“Intelligent community”which is a new concept built on the highly developed Internet and sensor networks has become more promising and meaningful.As an important part of the intelligent community,the technology is also of great use for the disabled health service.Based on the research of the theory of context-aware technology and the examples of international development applications,this paper designs an ontology based context-aware system framework named CADHS for disabled health service.The hierarchy based framework uses ontology to standardize and formalize context information and complete context modeling.This framework includes the collection and encapsulation of the original context information and constructs a formal reasoning model.Moreover,the framework provides query and subscription services as the external interface of the system.On the basis of this framework,the DHS-Protosystem(Disabled Health Service Protosystem)is designed and implemented.This paper introduces implementation of query and subscription service module.